Testing for nonlinearity in European climatic time series by the method of surrogate data
Testing for nonlinearity in European climatic time series by the method of surrogate data
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DOI：
10.1007/s00704-005-0130-7
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发表时间：
2006-01-01
影响因子：
3.4
通讯作者：
Raidl, A
中科院分区：
文献类型：
--
作者：
Miksovsky, J;Raidl, A
利用捷克气象站和NCEP/NCAR再分析系列的温度和压力记录，我们测试了单变量和多变量气候时间序列中可检测到的非线性的存在。替代数据的方法被用于非线性检测-将原始序列的非线性预测结果与非线性结构随机化的序列的结果进行比较。通过重构相空间中的局部线性模型进行预测。在单变量序列中没有发现或发现很弱的非线性，并且压力序列通常比温度序列（日平均值、最低值或最高值）表现出更强的非线性。在所有测试的多变量系统中发现了明显的非线性，特别是当同时使用温度和压力来形成相空间时。对30年和10年的数据集进行了非线性测试，非线性行为在较长版本中通常更明显。此外，测试系统表现出更实质性的非线性时，短期预测的成功被用作判别统计;随着预测时间的增加，可检测的非线性变得越来越弱，它完全消失的长期预测。
Using temperature and pressure records from Czech meteorological stations and NCEP/NCAR reanalysis series, we tested for the presence of detectable nonlinearity in univariate and multivariate climatic time series. The method of surrogate data was utilized for nonlinearity detection - results of nonlinear prediction for the original series were compared to the results for series whose nonlinear structure was randomized. The prediction was done by means of local linear models in the reconstructed phase space. None or very weak nonlinearity was found in the single (univariate) series, and pressure series generally exhibited stronger nonlinearity than series of temperature (daily mean, minimum or maximum). Distinct nonlinearity was found in all tested multivariate systems, especially when both temperatures and pressures were used simultaneously to form the phase space. Nonlinearity tests were carried out for 30-year and 10-year-long datasets and nonlinear behavior was generally more apparent in the longer versions. In addition, the tested systems showed more substantial nonlinearity when the success of short-range prediction was used as the discriminating statistic; with an increase of the prediction time, detectable nonlinearity became weaker and it disappeared completely for long-term prediction.